Fractional-Order Modeling of the Depth of Analgesia as Reference Model for Control Purposes

Autor: Cristina I. Muresan, Erwin T. Hegedüs, Marcian D. Mihai, Ghada Ben Othman, Isabela Birs, Dana Copot, Eva Henrietta Dulf, Robin De Keyser, Clara M. Ionescu, Martine Neckebroek
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Fractal and Fractional, Vol 8, Iss 9, p 539 (2024)
Druh dokumentu: article
ISSN: 2504-3110
DOI: 10.3390/fractalfract8090539
Popis: Little research has been carried out in terms of modeling and control of analgesia. However, emerging new technology and recent prototypes paved the way for several ideas on pain modeling for control. Recently, such an idea has been proposed for measuring the Depth of Analgesia (DoA). In this paper, that solution is further exploited towards obtaining a novel fractional-order model and dedicated controller for DoA. First, clinical data from patients undergoing general anesthesia are used to determine a commensurate fractional-order model of the skin impedance at each sampling period. Second, we provide a proof of concept indicating that fractional order changes due to variations in the infused opioid drug (Remifentanil). Third, a fractional-order model for DoA is developed correlating the changes in the pain index (as the output signal) and the Remifentanil infusion rate (as the input signal). Standard optimization routines are used to estimate the parameters. A database of 19 real patients is used. Lastly, a preliminary fractional-order controller is designed and tested in simulation for the 19 patients. The closed-loop simulation results correspond to the expected clinical outcomes.
Databáze: Directory of Open Access Journals
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